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Databricks Lakehouse Platform
What do you like best about the product?
It brings a lot of things together under one area to simplify operations in data engineering and data science. Databricks has enabled me to learn a lot of various topics in data engineering and data science because of their great training modules. The scalability of the Databricks Lakehouse is also very attractive. DLT Pipelines are also a great tool for ETL that I have loved using.
What do you dislike about the product?
The Databricks Lakehouse is very expensive, although I find it to be largely worth it for our situation because our team and company can utilize all of the tools they offer.
What problems is the product solving and how is that benefiting you?
Using DTL for a declarative approach to DLT has been very convenient and efficient for our Data Engineering processes. Running machine learning models in Databricks spark clusters grants efficient use of compute and faster model training times.
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Best orchestration platform
What do you like best about the product?
Databricks lakehouse helped us orchestre data for around 5000 data pipelines. It is very easy as it is config driven framework. We got onboarded easily migrated from airflow
What do you dislike about the product?
The documentation can be made more better. When it was new there was not enough documentation.
What problems is the product solving and how is that benefiting you?
Orchestration and data governance
Fast and Time saving processes
What do you like best about the product?
Making tasks easy and quick, Real time monitoring just on so easy
What do you dislike about the product?
Nothing , I like all the processes and their marketing strategies
What problems is the product solving and how is that benefiting you?
Real Time analysis of everyday store devices data within 15 min interval
Amazing platform
What do you like best about the product?
Easy to use and to ML and data engineers to work
What do you dislike about the product?
Little confusion on the last few updates
What problems is the product solving and how is that benefiting you?
Demand forecasting and data structuring
Beast When It Comes To Data On Cloud
What do you like best about the product?
1. ACID compliance on Data Lake which saves not only cost for storage but makes queries faster.
2. Customizable as per budget (by use of correct cluster sizing and other ways)
3. Init Scripts is really a boon if used correctly.
2. Customizable as per budget (by use of correct cluster sizing and other ways)
3. Init Scripts is really a boon if used correctly.
What do you dislike about the product?
1. Clusters often take up a lot of time to start up.
2. Many bugs were encountered personally on the new Unity Catalogue feature.
3. Missing Information Schema on Hive_Metastore.
2. Many bugs were encountered personally on the new Unity Catalogue feature.
3. Missing Information Schema on Hive_Metastore.
What problems is the product solving and how is that benefiting you?
The primary problem that Databricks Lakehouse Platform is solving is storing and processing big data. With its support of a wide variety of languages like Python, Scala, Sql etc it becomes mighty and helpful to process data. Role-based access management is a blessing for data governance.
Databricks is the heart of our IAplatform which allows experimentation and industrialization
What do you like best about the product?
We have been using Azure data bricks for over three years. The evolution of data bricks is impressive, as well as its stability. When our users (data engineer, data scientist) want a new feature, it very often happens that within a week or three months, this feature is developed by the Databricks team. Magic
What do you dislike about the product?
As a user, if you want to keep pace with the new features and capacity of the platform, you have to stop sleeping :) And yet the documentation is abundant, and the media is of good quality.
What problems is the product solving and how is that benefiting you?
Sentiment detection use cases, anomaly/fraud detection, risky customer detection. By associating it with cognitive services, identity document recognition use cases, kyc.
Very Powerful Tool
What do you like best about the product?
Unified Data Platform
Apache Spark Power
Machine Learning Capabilities
Scalability and Elasticity
Data Integration and Connector
Unity Catalog and Data Governance
These are a few key points on what I like most about Databricks.
Apache Spark Power
Machine Learning Capabilities
Scalability and Elasticity
Data Integration and Connector
Unity Catalog and Data Governance
These are a few key points on what I like most about Databricks.
What do you dislike about the product?
Computations are costly
Dependency on Cloud Infrastructure
Limited Offline access
As of now, I can think of these points on what I dislike about Databricks Platform
Dependency on Cloud Infrastructure
Limited Offline access
As of now, I can think of these points on what I dislike about Databricks Platform
What problems is the product solving and how is that benefiting you?
Mostly, I use this tool to create Data Pipelines using Apache Spark. And it also gives us the capability to connect Databricks to Tableau for Data Visualisation directly.
Best all-in-one Data Platform environment
What do you like best about the product?
By providing a fully-managed, highly performant and customizable Spark environment along with regular top-tier productivity features, Databricks is undeniably the most complete Data Platform in the market. My favorites features would be :
* Unity Catalog that provides colum-level lineage and a centralized access right management service
* Delta Live Table that provides easy to implement Data Quality control and monitoring
* Extensive CLIs that gives freedom in chosing your CI/CD platform
* Clusters policies that allows a better cost control
* Unity Catalog that provides colum-level lineage and a centralized access right management service
* Delta Live Table that provides easy to implement Data Quality control and monitoring
* Extensive CLIs that gives freedom in chosing your CI/CD platform
* Clusters policies that allows a better cost control
What do you dislike about the product?
The offline development can be improved. The recently release of a VsCode Extension and also Spark connect are steps towards this but still needs more features to be satisfying.
What problems is the product solving and how is that benefiting you?
Databricks helps us develop and deploy Data Products and train Machine Learning models more successfully in production, in very short amount of time, a secured environment and with controlled costs management.
Its compatibility with infrastructure-as-code tools such as Terraform also allows us to easily reproduce our standards accross multiple instances.
The integration with Azure Active Directory also eases the adoption and Access Control of resources and data assets.
Its compatibility with infrastructure-as-code tools such as Terraform also allows us to easily reproduce our standards accross multiple instances.
The integration with Azure Active Directory also eases the adoption and Access Control of resources and data assets.
Best implementation of Lakehouse Architecture
What do you like best about the product?
It provides a brilliant view of the entire data journey. It is a one-stop solution or a unified platform for all related Data Science and Analytics activities. Do not see any alternative product in the market offering such capabilities.
What do you dislike about the product?
Need a much larger Databricks community for discussions and clarifications.
What problems is the product solving and how is that benefiting you?
It helps in Model experimentation and bringing out the best accurate model for usage. It is also supporting the models to be deployed for serving clients. The turnaround time for the requests has been significantly less, which has increased the performance of our system.
Streamlining Data Management: My Experience with Databricks Lakehouse Platform
What do you like best about the product?
One of the primary benefits of Databricks Lakehouse Platform is its ability to unify data warehousing, data lakes, and streaming into a single, comprehensive platform. This allows users to easily access and analyze data from multiple sources in one place, improving efficiency and reducing complexity.
Another advantage is the platform's scalability and flexibility, which allows organizations to handle large volumes of data and adjust to changing business needs. Databricks Lakehouse Platform also offers powerful analytics and machine learning capabilities that enable users to gain deeper insights and make data-driven decisions.
In addition, the platform provides collaborative features that allow teams to work together on data-related projects, facilitating knowledge sharing and improving productivity. The platform's security and compliance features also ensure that data is protected and meets regulatory requirements.
Overall, Databricks Lakehouse Platform is a powerful tool that offers many benefits to organizations, including unified data management, scalability, flexibility, analytics, machine learning, collaboration, and security.
Another advantage is the platform's scalability and flexibility, which allows organizations to handle large volumes of data and adjust to changing business needs. Databricks Lakehouse Platform also offers powerful analytics and machine learning capabilities that enable users to gain deeper insights and make data-driven decisions.
In addition, the platform provides collaborative features that allow teams to work together on data-related projects, facilitating knowledge sharing and improving productivity. The platform's security and compliance features also ensure that data is protected and meets regulatory requirements.
Overall, Databricks Lakehouse Platform is a powerful tool that offers many benefits to organizations, including unified data management, scalability, flexibility, analytics, machine learning, collaboration, and security.
What do you dislike about the product?
For example, some users may find that the platform can be complex and may require a certain level of technical expertise to fully utilize its capabilities
What problems is the product solving and how is that benefiting you?
One of the key problems that Databricks Lakehouse Platform addresses is the challenge of managing and analyzing large volumes of data from various sources. The platform unifies data warehousing, data lakes, and streaming into a single, comprehensive platform, making it easier for organizations to access and analyze data from different sources in one place.
Another problem that Databricks Lakehouse Platform solves is the difficulty of integrating different data management and analytics tools. By providing a unified platform for data management, analytics, and machine learning, Databricks Lakehouse Platform eliminates the need for multiple tools and simplifies the integration process.
Another problem that Databricks Lakehouse Platform solves is the difficulty of integrating different data management and analytics tools. By providing a unified platform for data management, analytics, and machine learning, Databricks Lakehouse Platform eliminates the need for multiple tools and simplifies the integration process.
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